Zheng, ChunpingChen, XuZhang, HuayangChai, Ching Sing2024-05-302024-05-302024-06-01Zheng, C., Chen, X., Zhang, H., & Chai, C. S (2024). Automated versus peer assessment: Effects on learners’ English public speaking. Language Learning & Technology, 28(2), 210–228. https://hdl.handle.net/10125/735771094-3501https://hdl.handle.net/10125/73578This quasi-experimental research investigates the employment of a formative assessment platform aided by artificial intelligence in an English public speaking course. The platform integrates deep learning, automatic speech recognition, and automatic writing evaluation. It provides automated assessment and immediate feedback on speakers’ public speaking anxiety and their speaking and writing competence. Fifty-two English public speaking learners were randomly assigned to two groups. The control group (G1) undertook self-, peer, and teacher assessment via the platform, while the experimental group (G2) experienced self-, automated, and teacher assessment. The ANCOVA results revealed that students in G1 perceived significantly higher social engagement than those in G2, which indicates that social interaction between learners during peer assessment cannot be substituted by automated assessment. The chi-square analysis showed students’ different concerns regarding online formative assessment. While students in G1 showed concerns for peers’ qualifications and willingness to provide feedback, students in G2 suggested generating more detailed automated feedback to improve self-learning. No significant differences were found in learners’ English public speaking self-efficacy, engagement, or competence. This indicates that automated assessment can serve as an effective strategy for formative assessment and that AI tools may supplement peers as reliable learning companions in the foreseeable future.228Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International LicenseAutomated AssessmentPeer AssessmentEnglish Public SpeakingLearner EngagementSelf-efficacyArticle